Lucca Caiaffa Santos Rosa, Caio Oliveira Argolo, Cayque Monteiro Castro Nascimento and Andre Silva Pimentel*,
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引用次数: 0
Abstract
The local interpretable model-agnostic explanation (LIME) method was used to interpret two machine learning models of compounds penetrating the blood–brain barrier. The classification models, Random Forest, ExtraTrees, and Deep Residual Network, were trained and validated using the blood–brain barrier penetration dataset, which shows the penetrability of compounds in the blood–brain barrier. LIME was able to create explanations for such penetrability, highlighting the most important substructures of molecules that affect drug penetration in the barrier. The simple and intuitive outputs prove the applicability of this explainable model to interpreting the permeability of compounds across the blood–brain barrier in terms of molecular features. LIME explanations were filtered with a weight equal to or greater than 0.1 to obtain only the most relevant explanations. The results showed several structures that are important for blood–brain barrier penetration. In general, it was found that some compounds with nitrogenous substructures are more likely to permeate the blood–brain barrier. The application of these structural explanations may help the pharmaceutical industry and potential drug synthesis research groups to synthesize active molecules more rationally.
期刊介绍:
ACS Chemical Neuroscience publishes high-quality research articles and reviews that showcase chemical, quantitative biological, biophysical and bioengineering approaches to the understanding of the nervous system and to the development of new treatments for neurological disorders. Research in the journal focuses on aspects of chemical neurobiology and bio-neurochemistry such as the following:
Neurotransmitters and receptors
Neuropharmaceuticals and therapeutics
Neural development—Plasticity, and degeneration
Chemical, physical, and computational methods in neuroscience
Neuronal diseases—basis, detection, and treatment
Mechanism of aging, learning, memory and behavior
Pain and sensory processing
Neurotoxins
Neuroscience-inspired bioengineering
Development of methods in chemical neurobiology
Neuroimaging agents and technologies
Animal models for central nervous system diseases
Behavioral research